Driving Decisions with Data: Delight or Disaster?

Albert Einstein has been quoted as saying, “Not everything that counts can be counted, and not everything that can be counted counts.” Whether Einstein actually said this or not, he certainly embodied the sentiment by recognizing the value of using data to drive decisions. In fact, recent Forbes and TechJury studies have estimated that more data was created in a single minute in 2020 than the data created during Einstein’s entire life. How can all that data be put to use? Should it be driving our decision-making? To that point, in a 2018 Forrester survey of more than a thousand US companies, 91% of them said that data-driven decision-making was important to their business, while only 57% said they actually used data to make decisions in their business.

How do we bridge this gap? What do KPIs have to do with ROI? How do you get from being in “data denial” to being data driven? Why should you even care? This session will answer those questions and much more. Come see the relevance of the four V’s of Big Data. Discover three types of cognitive biases and how they are the enemies of opportunity. Are qualitative and quantitative data opposed to each other, or can they be friends? With regards to best practices for driving business decisions with data, find out how you should LOOK, LINK, LISTEN, LEVERAGE, and LEARN -- and how to make it all a delight rather than a disaster.

𝙇𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝙊𝙗𝙟𝙚𝙘𝙩𝙞𝙫𝙚𝙨: The participant/attendee will...
* Recognize how to leverage both qualitative data and quantitative data in driving business decision-making
* Identify the three types of cognitive biases in big data and how they’re the enemy of opportunity
* Define the five best practices for driving business decisions with data along with the key words for each one (look, link, listen, leverage, and learn)

Dr. Joe Perez

Award-winning International Keynote Speaker / Senior Systems Analyst / 2021 Thought Leader of the Year / Fractional CTO / Innovation Specialist (Bringing Data to Life and Life to Data!)

Raleigh, North Carolina, United States

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